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Bayesian-Regression-Tutorial

Bayeian modeling has become more and more popular, hoever, there are very few tutorials that explain the mathematical concepts regarding the estimation of these models that go into great detail. The PDF file attempts to fill this gap and the associated Python code puts the math into practice.

The Jypyter notebook puts the mathematics in the paper into code.

Update: 2/15/2022

I have added Julia code to the repository that codes the Gibbs sampler for the normal linear regression model. Comments and questions are appreciated.

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A tutorial on Bayesian regression modeling

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